Control infrastructure for enterprise AI agents.

AethosHub builds self-hosted software for governing how AI agents and applications access models, MCP tools, and enterprise systems. Protect credentials, enforce runtime policies, control tool permissions, and maintain auditable activity while keeping deployment and provider accounts within your environment.

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EnterpriseGrade Security

ScalableArchitecture

AuditableActivity Records

Agent Governance

One governed control layer between AI agents and enterprise systems.

Agent Access Manager is a self-hosted AI gateway and MCP security layer that governs how agents access models, tools, APIs, and internal systems. Agents and applications authenticate with scoped, revocable credentials while provider and enterprise secrets remain encrypted and hidden from agent code.

Every request can be evaluated against identity, team, model, tool, budget, rate, and guardrail policies before it is forwarded. The Private MCP Registry centralizes approved servers, while role-based access brokerage determines which agents, keys, and teams can use individual tools.

For self-hosted MCP servers, the Kubernetes MCP Orchestrator manages isolated deployments, configuration, secrets, runtime status, logs, and restart operations. Agent Access Manager records gateway activity, MCP tool calls, policy decisions, and outcomes, giving security and platform teams a consistent operational and audit trail.

Agent Access01 / 06

Scoped agent access

Identify agents and applications through revocable credentials associated with owners, teams, environments, and access policies.

Scoped access context

Credential Security02 / 06

Credential protection

Store provider and MCP credentials encrypted and inject them only when authorized requests are executed. Agents do not receive reusable provider keys.

Protected credentials

Access Policy03 / 06

Runtime authorization

Authorize model requests and MCP tool access using agent, key, team, server, and tool assignments before forwarding calls.

Request authorization

Activity Records04 / 06

Auditable activity

Record gateway requests, MCP tool calls, policy decisions, and outcomes handled through Agent Access Manager.

Operational audit trail

Policy Enforcement05 / 06

Runtime guardrails

Apply configured policies for content, PII, secrets, providers, spend, rate limits, and tool access to requests and responses.

Configured guardrails

MCP Operations06 / 06

MCP orchestration

Deploy and operate self-hosted MCP servers in Kubernetes with isolated runtimes, configuration injection, logs, status, and restart controls.

Managed MCP runtimes

AI Agents

Govern coding agents and tool access

Connect internally developed agents

Control agent-to-model communication

Control agent-to-tool communication

Agent Access Manager

Authenticate agents with scoped credentials

Authorize model and tool requests

Keep provider credentials hidden from agents

Enforce guardrails before forwarding requests

Record policy decisions and outcomes

Enterprise Systems

Connect approved cloud applications

Govern API integrations

Protect access to structured data

Control internal business tools

Govern MCP servers and endpoints

Products

Central control for your AI infrastructure.

Flagship platform

agentaccessmanager.com

Agent Access ManagerBy AethosHub

One governed gateway for model and MCP access. Provider credentials remain hidden from agents.

Agent Access Manager runs in your environment between AI applications, agents, model providers, and MCP tools. Applications use an OpenAI-compatible endpoint and scoped virtual keys while the platform routes requests, protects provider credentials, enforces policies, and records governed activity.

Scoped virtual access

Create revocable, provider-independent virtual keys for applications, teams, and agents. Provider credentials remain encrypted and are not returned to clients.

Compatible model access

Connect OpenAI-compatible clients to the gateway, use model aliases, and reduce provider-specific integration changes.

Health-aware routing

Route model requests through configured providers and fail over when a provider or deployment becomes unavailable.

Budgets and rate controls

Enforce spend budgets and RPM/TPM limits across organizations, teams, projects, and keys.

Request and response guardrails

Apply configured PII, secret, pattern, and content policies to requests and responses with allow, flag, redact, or block actions.

MCP access governance

Security visibility

Maintain searchable gateway and MCP activity records for operational investigation, security detection, and response workflows.

Explore Agent Access Manager

app.ts — OpenAI-compatible client example

const client = new OpenAI({
  baseURL: "https://gateway.acme.com/v1",
  apiKey: process.env.VIRTUAL_KEY,  // not a vendor key
});

const reply = await client.chat.completions.create({
  model: "fast",  // your alias — routed, metered, guarded
  messages: [{ role: "user", content: "Review this contract." }],
});

OpenAI-compatibleSelf-hostedConfigurable base URL

ProductComing soon

apikeyops.com

Centralize ownership and lifecycle visibility for enterprise AI credentials.

APIKeyOps provides a governed inventory of provider credentials, their owners, lifecycle status, and available usage information. It helps security and platform teams identify unmanaged credentials, assign accountability, and maintain an auditable operational record.

Credential inventory

Track provider credentials as governed assets with ownership and lifecycle status.

Ownership and accountability

Associate credentials with the teams, projects, and environments responsible for their use.

Usage visibility

Attribute available provider usage and cost information to the appropriate credentials and owners.

Lifecycle oversight

Track expiry, rotation, stale, and revoked states where supported by the configured provider integration.

Audit history

Record security-relevant credential events to support internal security and compliance reviews.

APIKeyOps coming soon

Integrations

Connect model providers and agent frameworks through one governed layer.

Bring supported model providers, OpenAI-compatible endpoints, and agent frameworks behind a consistent gateway. Centralize routing, credentials, policies, and audit visibility without rebuilding governance separately for every application.

LLM Provider Support

Leading model providers through governed connections.

Connect OpenAI-compatible endpoints, Anthropic, Gemini, Vertex AI, and supported self-hosted models through centrally managed provider configurations and model aliases.

OpenAIAnthropicAzure OpenAIAWS BedrockGoogle GeminiVertex AICohereMistral AIGroqOllamaMeta LlamaIBM watsonxNVIDIADatabricksDeepSeek

Additional providers can connect through supported OpenAI-compatible endpoints.

Framework Support

Works with OpenAI-compatible clients and common agent frameworks.

Connect SDKs, frameworks, internal wrappers, and AI applications that support a configurable OpenAI-compatible endpoint.

LangChainLangGraphLlamaIndexDSPyVercel AI SDKLiteLLMSemantic KernelOpenAI SDKCrewAIAGAutoGen

Integration typically requires configuring the Agent Access Manager base URL and a scoped virtual key.

See supported integrations

Standardize security across your entire AI infrastructure.

Talk directly with the engineers who build Agent Access Manager. We will review your model providers, agent workflows, MCP servers, deployment environment, and security requirements, then map them to a practical control architecture.

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We typically respond within one business day.